An ongoing trend in modem wireless communication systems is to further increase the transmit data rates to enable the use of multimedia applications (e.g., those involving video and/or audio content) by wireless user equipment. The use of multiple transmit and receive antennas has been proposed, for example, in 3GPP (Third Generation, Partnership Project) discussions as a means to increase the data transmission rates. However, it can be appreciated that the use of multiple transmit antennas, where each antenna transmits an independent data stream using the same spreading sequence as the other antennas, will inevitably result in inter-antenna interference. The inter-antenna interference must be mitigated in order to successfully receive the transmitted data. In addition, other sources of interference can also deteriorate the performance of the receiver system. For example, multiple access interference (MAI) can be detrimental to receiver performance. In general, MAI is the signal interference experienced by the signal of the desired physical channel due to the presence of signals of other physical channels.
One of the main differences between inter-antenna interference and MAI is that the correlation with the spreading sequence at the receiver suppresses MAI by an amount that is a function of the spreading factor, while the variance of the inter-antenna interference remains substantially constant, and is not suppressed by the despreading process since it is induced by signals employing the same spreading sequence as the desired signal.
In a conventional code division, multiple access (CDMA) receiver, that is, in a conventional rake receiver, the receiver collects and combines only the received multipath signals. It is well known that a linear minimum mean square error (LMMSE) multi-user detector (MUD) has been developed for CDMA terminal receivers. However, adaptive versions of LMMSE MUD require the use of spreading sequences with a short period and, thus, LMMSE MUD is not appropriate for use in modem wideband CDMA (WCDMA) terminals.
Other types of receivers (other than rake) that are suitable for the reception of a WCDMA multiple input multiple output (MIMO) signal can be divided into two broad categories, namely, advanced WCDMA receivers and MIMO receivers. Advanced WCDMA receivers operate to provide additional suppression of MAI, while so-called MIMO receivers mitigate mainly inter-antenna interference. However, the advanced WCDMA receivers known to the inventors do not efficiently mitigate inter-antenna interference, and the majority of the MIMO receivers known to the inventors ignore the presence of MAI in their signal processing circuitry and algorithms.
More specifically, advanced WCDMA receivers either suppress or cancel MAI, thus achieving enhanced performance when compared to the conventional rake CDMA receiver. Those receiver architectures that provide for the suppression of MAI are considered as a more viable option for use in the WCDMA downlink (the direction towards the WCDMA user terminal equipment). It is noted that MAI can be divided into inter-cell and intra-cell interference. The inter-cell interference can be suppressed in the spatial domain, that is, with multiple receive antennas, while the intra-cell interference can be suppressed in the temporal domain. To achieve these goals two approaches have been proposed.
A first approach uses a linear channel equalizer that restores the orthogonality of physical channels, thus suppressing intra-cell interference while suppressing inter-cell interference in the spatial domain. The linear channel equalizer approximates the LMMSE MUD by ignoring the correlations between the spreading sequences in the received signal covariance matrix. In the case of single transmit antenna, the approximation results in good performance with a reasonable implementation complexity. The channel equalization can be implemented either at the CDMA signal chip level, prior to the correlation with the spreading sequence, or at the symbol (multi-chip) level. In the following discussion the chip level implementation is considered. Several adaptive algorithms have been proposed for use in the linear channel equalizer. For example, an overview of adaptive solutions is presented in K. Hooli, M. Juntti, M. Heikkilä, P. Komulainen, M. Latva-aho, and J. Lilleberg, “Chip-level channel equalization in WCDMA downlink,” Eurasip J. Applied Sign. Proc. 2002, p. 757-770.
A generalized rake receiver (see, for example, G. Bottomley, T. Ottoson, and Y. P. Wang, “A generalized RAKE receiver for interference suppression,” IEEE J. Selected Areas in Comm. 18, p. 1536-1545) approximates a matched filter in colored noise. Additional rake fingers (decorrelators) are allocated in the generalized rake receiver to process those delays that do not correspond to multipath delays. It has, been shown that the linear, channel equalizer and the generalized rake receiver are equivalent receivers under certain conditions.
A second approach is to suppress the inter-antenna interference (IAI) using the MIMO receiver architecture. For example, one proposed MIMO receiver is a Vertical BLAST (Bell Laboratories Layered SpaceTime), or V-BLAST, receiver for use in rich scattering MIMO environments (see P. Wolniansky, G. Foschini, G. Golden and R. Valenzuela, “V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel,” in Proc. URSI Int. Symp. Sign., Syst. and Electr., September 1998, p. 295-300). In the BLAST approach the transmitted signal is received one layer at time, i.e., one transmit antenna at time, and all other layers are nulled with a zero-forcing algorithm. After the first layer is demodulated, the signal is re-modulated and cancelled from the received signal, which enhances the signal-to-interference-plus-noise ratio (SINR). This procedure is repeated after all layers are received. Variants of the V-BLAST approach have also been proposed. In some variants MAI is suppressed with a filter that precedes the BLAST structure for mitigating inter-antenna interference.
Another option is to use different approximations of maximum a posteriori (MAP) detection. In a MAP detector the decision of a transmitted bit (a one or a zero decision) is performed after exhaustive and complex calculations are performed, during which a most probable transmitted bit is determined based on a priori probabilities of the bit and the received signal (see A. Hottinen, O. Tirkkonen and R. Wichman, “Multi-antenna Transceiver Techniques for 3G and Beyond”, John Wiley & Sons, Chichester, UK, 2003). However, the approximations of MAP or maximum-likelihood sequence detection (MLSD) approaches have a considerable implementation complexity. The implementation complexity of the MLSD or MAP approximations can be a disadvantage when embodied in a battery powered user terminal that may have data processor speed and operating power consumption limitations.